The present invention relates generally to risk assessment and, in particular, utilizing nonparametric risk assessment to estimate a failure probability for tools.
Exploration and production of hydrocarbons or geothermal energy requires that accurate and precise measurements be performed on earth formations, which may contain reservoirs of the hydrocarbons or geothermal energy. Some of these measurements are performed at the surface of the earth and may be referred to as surveys. Other measurements are generally performed in boreholes penetrating the earth formations. The process of performing these measurements in boreholes is called “well logging.”
In one example of well logging, a logging tool, used to perform the measurements, is lowered into a borehole and supported by a wireline. The logging tool contains various components that perform the measurements and record or transmit data associated with the measurements. Of course, the logging tool may be any tool that is may be utilized while drilling.
Various types of measurements can be performed in a borehole. One type of measurement that may be made relates to stresses to which the tool is exposed while in operation. These stresses may include, but are not limited to, lateral vibration, temperature and the length of time to which the tool is exposed to these stresses.
In traditional, reliability driven risk assessment, the reliability of a system is mostly defined as a function of time, where time may be quantified by elapsed time, use time, or number of cycles. While this approach has resulted in improvements in overall risk assessment in many different industries, it has limited viability in the drilling industry since tool health is heavily influenced by the stresses to which a tool is exposed.
Most reliability based risk analysis techniques are founded on the premise that, given a sample of failure times, it is possible to derive a probability distribution function that quantifies the reliability as a function of time. In such distributions, time is most often expressed in terms of use time, elapsed time, or as a number of cycles. From the distributions, it is possible to estimate a range of values such as reliability and failure probability. As used herein, the term “risk” may be used interchangeably with many different metrics related to reliability, such as reliability, failure probability, hazard rate, etc.
This approach has been successfully used in many industries, but the unique nature of the drilling industry is such that having a function that simply maps time to risk is not enough. For the most part, the implemented prior art methods have been limited to simple time based statistics that in no way account for the observed stresses. There has been some limited work related to incorporating different stress signals into the assessment process, but it has yet to produce a method that is capable of accurately estimating the risk of failure for an individual tool that has been exposed to a particular sequence of stresses.